Doses of Gsk3 Inhibitor :0,1.5,3,6,12,24 uM
Treatment durtaion : 30 min
Quantification steps :

I use the mean signal of each gel to normalize the signal values across the gels : I had done it by two methods to cross-chek results.Both give almost the same values. I have selected M2 for plotting :
M1 : I divide Signal by total(protein/stain) for each well. Then I normalize each of these Signal_by_Total over the mean Signal_by_Total.
M2 : I divide Signal of each well by mean signal for the gel. Similarly,I divide total(protein/stain) of each well by mean total(protein/stain) for the gel. Then I divide normalized signal for each well over the normalized total(protein/stain) for that well.

Libraries_InputDirectoryPath

## Loading required package: lattice
## Loading required package: plyr
## 
## Attaching package: 'ggpubr'
## The following object is masked from 'package:plyr':
## 
##     mutate
## Loading required package: gridExtra
## 
## Attaching package: 'egg'
## The following object is masked from 'package:ggpubr':
## 
##     ggarrange
## 
## Attaching package: 'dplyr'
## The following object is masked from 'package:gridExtra':
## 
##     combine
## The following objects are masked from 'package:plyr':
## 
##     arrange, count, desc, failwith, id, mutate, rename, summarise,
##     summarize
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
## Warning in dir.create("./OutputFiles"): './OutputFiles' already exists

Functions

Function ReadInWBData : In case of GSK3i_pAkt, need leave out some lanes since there was a smear in Gel23.
I am using only the mean of R3 samples on Gel23 & only the mean of R2 samples on Gel22. In other cases I’ll use the mean of the whole gel as long as the samples on each of the gels from which data is aggregated are the same.

pAkt

Gel1(R1)

image_files = c("0001720_02_JuneGel1_CTDR_Aktp.png")

knitr::include_graphics(file.path(image_folder,image_files[1]))

Gel22(R2)

image_files = c("0000062_02_JuneGel22_CTDR_Aktp.png")

knitr::include_graphics(file.path(image_folder,image_files[1]))

Gel23(R3)

image_files = c("0000063_02_JuneGel23_CTDR_Aktp.png")

knitr::include_graphics(file.path(image_folder,image_files[1]))

pAkt_Akt : Reading in Data, Normalization and FC calculation pAkt_Akt : Reading in Data, Normalization and FC calculation

RawValues_Normalization

Raw values : Phospho protein and total protein

In Gel23 , there are values for only 17 wells, because two lanes that had smears were not inluded. However the lane number is not corretly specified since, this plot was just an exploratory plot made for myself.

########## Normalization over Common sample

# Plot_RawValues(CTDR_Akt_NormOCom_all,
#                Well_no,
#                phosP,
#                Mean_Com_phosP)
# 
# Plot_RawValues(CTDR_Akt_NormOCom_all,
#                Well_no,
#                totalP,
#                Mean_Com_totalP)

Normalization : Over Common Sample and over mean of replicate

########## Normalization over Common sample
# 
# Plot_NormValues_Check(CTDR_Akt_NormOCom_all,
#                       Well_no,
#                       phosP_Norm_oCom)


########## Normalization over Mean 

# Plot_NormValues_Check(CTDR_Akt_NormOMeanRep,
#                       Well_no,
#                       phosP_Norm_oMeanRep)

M1 and M2

Plot_NormValues_Check(CTDR_Akt_NormOMeanRep,
                      Well_no,
                      Norm_phosP_by_total_M1)

Plot_NormValues_Check(CTDR_Akt_NormOMeanRep,
                      Well_no,
                      Norm_phosP_by_total_M2)

pAkt:NormOverAkt

M2

T-test:Unpaired

Ttest_pAkt_CTDR_Unpaired <- compare_means(Norm_phosP_by_total_M2 ~ Cell_line,
                                             data = CTDR_Akt_plot,
                                             method = "t.test",
                                             paired = FALSE,
                                             group.by = c("Treatment"),
                                             ref.group = NULL)

kable(Ttest_pAkt_CTDR_Unpaired)
Treatment .y. group1 group2 p p.adj p.format p.signif method
0.0 Norm_phosP_by_total_M2 XX XO 0.0068780 0.041 0.0069 ** T-test
1.5 Norm_phosP_by_total_M2 XX XO 0.0698290 0.130 0.0698 ns T-test
3.0 Norm_phosP_by_total_M2 XX XO 0.0190169 0.057 0.0190 * T-test
6.0 Norm_phosP_by_total_M2 XX XO 0.0088535 0.041 0.0089 ** T-test
12.0 Norm_phosP_by_total_M2 XX XO 0.0072185 0.041 0.0072 ** T-test
24.0 Norm_phosP_by_total_M2 XX XO 0.0654411 0.130 0.0654 ns T-test

Treatment Dose in Log2 scale log2(Treatment+1)

Treatment Doses as Factors

M1

T-test:Unpaired

# Ttest_pAkt_CTDR_Unpaired <- compare_means(Norm_phosP_by_total_M1 ~ Cell_line,
#                                              data = CTDR_Akt_plot,
#                                              method = "t.test",
#                                              paired = FALSE,
#                                              group.by = c("Treatment"),
#                                              ref.group = NULL)
# 
# kable(Ttest_pAkt_CTDR_Unpaired)

T-test:Paired

# Ttest_pAkt_CTDR_Paired <- compare_means(Norm_phosP_by_total_M1 ~ Cell_line,
#                                            data = CTDR_Akt_plot,
#                                            method = "t.test",
#                                            paired = TRUE,
#                                            group.by = c("Treatment"),
#                                            ref.group = NULL)
# 
# kable(Ttest_pAkt_CTDR_Paired)

Treatment Dose in Log2 scale log2(Treatment+1)

Treatment Doses as Factors

pAkt_Akt:FC over XX

M2

T-test:Unpaired

Ttest_pAkt_CTDR_Unpaired <- compare_means(FCoXX_M2 ~ Cell_line,
                                             data = CTDR_Akt_plot,
                                             method = "t.test",
                                             paired = FALSE,
                                             group.by = c("Treatment"),
                                             ref.group = NULL)

kable(Ttest_pAkt_CTDR_Unpaired)
Treatment .y. group1 group2 p p.adj p.format p.signif method
0.0 FCoXX_M2 XX XO 0.0068780 0.041 0.0069 ** T-test
1.5 FCoXX_M2 XX XO 0.0698290 0.130 0.0698 ns T-test
3.0 FCoXX_M2 XX XO 0.0190169 0.057 0.0190 * T-test
6.0 FCoXX_M2 XX XO 0.0088535 0.041 0.0089 ** T-test
12.0 FCoXX_M2 XX XO 0.0072185 0.041 0.0072 ** T-test
24.0 FCoXX_M2 XX XO 0.0654411 0.130 0.0654 ns T-test

Treatment Dose in Log2 scale log2(Treatment+1)

Treatment Doses as Factors

M1

T-test:Unpaired

Ttest_pAkt_CTDR_Unpaired <- compare_means(FCoXX_M1 ~ Cell_line,
                                             data = CTDR_Akt_plot,
                                             method = "t.test",
                                             paired = FALSE,
                                             group.by = c("Treatment"),
                                             ref.group = NULL)

kable(Ttest_pAkt_CTDR_Unpaired)
Treatment .y. group1 group2 p p.adj p.format p.signif method
0.0 FCoXX_M1 XX XO 0.0045633 0.023 0.0046 ** T-test
1.5 FCoXX_M1 XX XO 0.0749742 0.150 0.0750 ns T-test
3.0 FCoXX_M1 XX XO 0.0172491 0.069 0.0172 * T-test
6.0 FCoXX_M1 XX XO 0.0022758 0.014 0.0023 ** T-test
12.0 FCoXX_M1 XX XO 0.0267937 0.080 0.0268 * T-test
24.0 FCoXX_M1 XX XO 0.0869214 0.150 0.0869 ns T-test

T-test:Paired

Ttest_pAkt_CTDR_Paired <- compare_means(FCoXX_M1 ~ Cell_line,
                                           data = CTDR_Akt_plot,
                                           method = "t.test",
                                           paired = TRUE,
                                           group.by = c("Treatment"),
                                           ref.group = NULL)

kable(Ttest_pAkt_CTDR_Paired)
Treatment .y. group1 group2 p p.adj p.format p.signif method
0.0 FCoXX_M1 XX XO 0.0102556 0.062 0.010 * T-test
1.5 FCoXX_M1 XX XO 0.1807821 0.210 0.181 ns T-test
3.0 FCoXX_M1 XX XO 0.1042327 0.210 0.104 ns T-test
6.0 FCoXX_M1 XX XO 0.0322956 0.160 0.032 * T-test
12.0 FCoXX_M1 XX XO 0.0444666 0.180 0.044 * T-test
24.0 FCoXX_M1 XX XO 0.0472210 0.180 0.047 * T-test

Treatment Dose in Log2 scale log2(Treatment+1)

Treatment Doses as Factors

pAkt_Akt:FC over res cntrl

M2

T-test:Unpaired This comparison gave an error because the control replicate values were 1 ??

Ttest_pAkt_CTDR_Unpaired <- compare_means(FCoCntrl_M2 ~ Cell_line,
                                          data = CTDR_Akt_plot,
                                          method = "t.test",
                                          paired = FALSE,
                                          group.by = c("Treatment"),
                                          ref.group = NULL)

kable(Ttest_pAkt_CTDR_Unpaired)
Treatment .y. group1 group2 p p.adj p.format p.signif method
0.0 FCoCntrl_M2 XX XO 1.0000000 1 1.00 ns T-test
1.5 FCoCntrl_M2 XX XO 0.6895333 1 0.69 ns T-test
3.0 FCoCntrl_M2 XX XO 0.6187675 1 0.62 ns T-test
6.0 FCoCntrl_M2 XX XO 0.8166795 1 0.82 ns T-test
12.0 FCoCntrl_M2 XX XO 0.4948997 1 0.49 ns T-test
24.0 FCoCntrl_M2 XX XO 0.9457132 1 0.95 ns T-test

Treatment Dose in Log2 scale log2(Treatment+1)

Treatment Doses as Factors

M1

T-test:Unpaired This comparison gave an error because the control replicate values were 1 ??

Ttest_pAkt_CTDR_Unpaired <- compare_means(FCoCntrl_M1 ~ Cell_line,
                                          data = CTDR_Akt_plot,
                                          method = "t.test",
                                          paired = FALSE,
                                          group.by = c("Treatment"),
                                          ref.group = NULL)

kable(Ttest_pAkt_CTDR_Unpaired)
Treatment .y. group1 group2 p p.adj p.format p.signif method
0.0 FCoCntrl_M1 XX XO 1.0000000 1 1.00 ns T-test
1.5 FCoCntrl_M1 XX XO 0.6792163 1 0.68 ns T-test
3.0 FCoCntrl_M1 XX XO 0.5896125 1 0.59 ns T-test
6.0 FCoCntrl_M1 XX XO 0.7732120 1 0.77 ns T-test
12.0 FCoCntrl_M1 XX XO 0.5573437 1 0.56 ns T-test
24.0 FCoCntrl_M1 XX XO 0.9480569 1 0.95 ns T-test

T-test:Paired

Ttest_pAkt_CTDR_Paired <- compare_means(FCoCntrl_M1 ~ Cell_line,
                                           data = CTDR_Akt_plot,
                                           method = "t.test",
                                           paired = TRUE,
                                           group.by = c("Treatment"),
                                           ref.group = NULL)

kable(Ttest_pAkt_CTDR_Paired)
Treatment .y. group1 group2 p p.adj p.format p.signif method
0.0 FCoCntrl_M1 XX XO 1.0000000 1 1.00 ns T-test
1.5 FCoCntrl_M1 XX XO 0.7644804 1 0.76 ns T-test
3.0 FCoCntrl_M1 XX XO 0.7095662 1 0.71 ns T-test
6.0 FCoCntrl_M1 XX XO 0.8247507 1 0.82 ns T-test
12.0 FCoCntrl_M1 XX XO 0.5961830 1 0.60 ns T-test
24.0 FCoCntrl_M1 XX XO 0.8566883 1 0.86 ns T-test

Treatment Dose in Log2 scale log2(Treatment+1)

Treatment Doses as Factors

pP70s6k

Gel3(R1), Gel19(R2) and Gel20(R3)

image_files = c("0001725_02_JuneGel3_CTDR_p70S6K.png","0000584_02_JuneGel3_CTDR_TPS.png")
knitr::include_graphics(file.path(image_folder,image_files[1]))
knitr::include_graphics(file.path(image_folder,image_files[2]))

image_files = c("0000044_02_JuneGel19_CTDR_p70S6K.png","0000048_02_JuneGel19_CTDR_TPS.png")
knitr::include_graphics(file.path(image_folder,image_files[1]))
knitr::include_graphics(file.path(image_folder,image_files[2]))

image_files = c("0000045_02_JuneGel20_CTDR_p70S6K.png","0000049_02_JuneGel20_CTDR_TPS.png")
knitr::include_graphics(file.path(image_folder,image_files[1]))
knitr::include_graphics(file.path(image_folder,image_files[2]))

pP70s6k_TPS : Reading in Data, Normalization and FC calculation 

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * `` -> ...6
## * ...
## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * `` -> ...6
## * ...
## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * `` -> ...6
## * ...

RawValues_Normalization

Raw values : Phospho protein and total protein

########## Normalization over Common sample

# Plot_RawValues(CTDR_P70s6k_NormOCom_all,
#                Well_no,
#                phosP,
#                Mean_Com_phosP)
# 
# Plot_RawValues(CTDR_P70s6k_NormOCom_all,
#                Well_no,
#                totalP,
#                Mean_Com_totalP)

Normalization : Over Common Sample and over mean of replicate

For “Over Common Sample” : There were two samples that were on both gels(19 and 20). These were the untreated controls of both XX and XO cell line of Replicate1. So the mean of these common samples was used for normalization.

########## Normalization over Common sample

# Plot_NormValues_Check(CTDR_P70s6k_NormOCom_all,
#                       Well_no,
#                       phosP_Norm_oCom)
# 
# 
# ########## Normalization over Mean 
# 
# Plot_NormValues_Check(CTDR_P70s6k_NormOMeanRep,
#                       Well_no,
#                       phosP_Norm_oMeanRep)

M1 and M2

Plot_NormValues_Check(CTDR_P70s6k_NormOMeanRep,
                      Well_no,
                      Norm_phosP_by_total_M1)

Plot_NormValues_Check(CTDR_P70s6k_NormOMeanRep,
                      Well_no,
                      Norm_phosP_by_total_M2)

pP70s6k:NormOverP70s6k

M2

T-test:Unpaired

Ttest_pP70s6k_CTDR_Unpaired <- compare_means(Norm_phosP_by_total_M2 ~ Cell_line,
                                             data = CTDR_P70s6k_plot,
                                             method = "t.test",
                                             paired = FALSE,
                                             group.by = c("Treatment"),
                                             ref.group = NULL)

kable(Ttest_pP70s6k_CTDR_Unpaired)
Treatment .y. group1 group2 p p.adj p.format p.signif method
0.0 Norm_phosP_by_total_M2 XX XO 0.4676918 1 0.47 ns T-test
1.5 Norm_phosP_by_total_M2 XX XO 0.4010295 1 0.40 ns T-test
3.0 Norm_phosP_by_total_M2 XX XO 0.3207886 1 0.32 ns T-test
6.0 Norm_phosP_by_total_M2 XX XO 0.9346933 1 0.93 ns T-test
12.0 Norm_phosP_by_total_M2 XX XO 0.4274391 1 0.43 ns T-test
24.0 Norm_phosP_by_total_M2 XX XO 0.3300841 1 0.33 ns T-test

Treatment Dose in Log2 scale log2(Treatment+1)

Treatment Doses as Factors

M1

T-test:Unpaired

Ttest_pP70s6k_CTDR_Unpaired <- compare_means(Norm_phosP_by_total_M1 ~ Cell_line,
                                             data = CTDR_P70s6k_plot,
                                             method = "t.test",
                                             paired = FALSE,
                                             group.by = c("Treatment"),
                                             ref.group = NULL)

kable(Ttest_pP70s6k_CTDR_Unpaired)
Treatment .y. group1 group2 p p.adj p.format p.signif method
0.0 Norm_phosP_by_total_M1 XX XO 0.4698484 1 0.47 ns T-test
1.5 Norm_phosP_by_total_M1 XX XO 0.3783957 1 0.38 ns T-test
3.0 Norm_phosP_by_total_M1 XX XO 0.3201212 1 0.32 ns T-test
6.0 Norm_phosP_by_total_M1 XX XO 0.9376913 1 0.94 ns T-test
12.0 Norm_phosP_by_total_M1 XX XO 0.4373032 1 0.44 ns T-test
24.0 Norm_phosP_by_total_M1 XX XO 0.3378120 1 0.34 ns T-test

T-test:Paired

Ttest_pP70s6k_CTDR_Paired <- compare_means(Norm_phosP_by_total_M1 ~ Cell_line,
                                           data = CTDR_P70s6k_plot,
                                           method = "t.test",
                                           paired = TRUE,
                                           group.by = c("Treatment"),
                                           ref.group = NULL)

kable(Ttest_pP70s6k_CTDR_Paired)
Treatment .y. group1 group2 p p.adj p.format p.signif method
0.0 Norm_phosP_by_total_M1 XX XO 0.4811580 1 0.48 ns T-test
1.5 Norm_phosP_by_total_M1 XX XO 0.5266256 1 0.53 ns T-test
3.0 Norm_phosP_by_total_M1 XX XO 0.3120085 1 0.31 ns T-test
6.0 Norm_phosP_by_total_M1 XX XO 0.9568264 1 0.96 ns T-test
12.0 Norm_phosP_by_total_M1 XX XO 0.4704039 1 0.47 ns T-test
24.0 Norm_phosP_by_total_M1 XX XO 0.4570191 1 0.46 ns T-test

Treatment Dose in Log2 scale log2(Treatment+1)

Treatment Doses as Factors

pP70s6k_TPS:FC over XX

M2

T-test:Unpaired

Ttest_pP70s6k_CTDR_Unpaired <- compare_means(FCoXX_M2 ~ Cell_line,
                                             data = CTDR_P70s6k_plot,
                                             method = "t.test",
                                             paired = FALSE,
                                             group.by = c("Treatment"),
                                             ref.group = NULL)

kable(Ttest_pP70s6k_CTDR_Unpaired)
Treatment .y. group1 group2 p p.adj p.format p.signif method
0.0 FCoXX_M2 XX XO 0.4676918 1 0.47 ns T-test
1.5 FCoXX_M2 XX XO 0.4010295 1 0.40 ns T-test
3.0 FCoXX_M2 XX XO 0.3207886 1 0.32 ns T-test
6.0 FCoXX_M2 XX XO 0.9346933 1 0.93 ns T-test
12.0 FCoXX_M2 XX XO 0.4274391 1 0.43 ns T-test
24.0 FCoXX_M2 XX XO 0.3300841 1 0.33 ns T-test

Treatment Dose in Log2 scale log2(Treatment+1)

Treatment Doses as Factors

M1

T-test:Unpaired

Ttest_pP70s6k_CTDR_Unpaired <- compare_means(FCoXX_M1 ~ Cell_line,
                                             data = CTDR_P70s6k_plot,
                                             method = "t.test",
                                             paired = FALSE,
                                             group.by = c("Treatment"),
                                             ref.group = NULL)

kable(Ttest_pP70s6k_CTDR_Unpaired)
Treatment .y. group1 group2 p p.adj p.format p.signif method
0.0 FCoXX_M1 XX XO 0.4698484 1 0.47 ns T-test
1.5 FCoXX_M1 XX XO 0.3783957 1 0.38 ns T-test
3.0 FCoXX_M1 XX XO 0.3201212 1 0.32 ns T-test
6.0 FCoXX_M1 XX XO 0.9376913 1 0.94 ns T-test
12.0 FCoXX_M1 XX XO 0.4373032 1 0.44 ns T-test
24.0 FCoXX_M1 XX XO 0.3378120 1 0.34 ns T-test

T-test:Paired

Ttest_pP70s6k_CTDR_Paired <- compare_means(FCoXX_M1 ~ Cell_line,
                                           data = CTDR_P70s6k_plot,
                                           method = "t.test",
                                           paired = TRUE,
                                           group.by = c("Treatment"),
                                           ref.group = NULL)

kable(Ttest_pP70s6k_CTDR_Paired)
Treatment .y. group1 group2 p p.adj p.format p.signif method
0.0 FCoXX_M1 XX XO 0.4811580 1 0.48 ns T-test
1.5 FCoXX_M1 XX XO 0.5266256 1 0.53 ns T-test
3.0 FCoXX_M1 XX XO 0.3120085 1 0.31 ns T-test
6.0 FCoXX_M1 XX XO 0.9568264 1 0.96 ns T-test
12.0 FCoXX_M1 XX XO 0.4704039 1 0.47 ns T-test
24.0 FCoXX_M1 XX XO 0.4570191 1 0.46 ns T-test

Treatment Dose in Log2 scale log2(Treatment+1)

Treatment Doses as Factors

pP70s6k_TPS:FC over res cntrl

M2

T-test:Unpaired This comparison gave an error because the control replicate values were 1 ??

Ttest_pP70s6k_CTDR_Unpaired <- compare_means(FCoCntrl_M2 ~ Cell_line,
                                          data = CTDR_P70s6k_plot,
                                          method = "t.test",
                                          paired = FALSE,
                                          group.by = c("Treatment"),
                                          ref.group = NULL)

kable(Ttest_pP70s6k_CTDR_Unpaired)
Treatment .y. group1 group2 p p.adj p.format p.signif method
0.0 FCoCntrl_M2 XX XO 1.0000000 1.00 1.00 ns T-test
1.5 FCoCntrl_M2 XX XO 0.1872044 0.83 0.19 ns T-test
3.0 FCoCntrl_M2 XX XO 0.2393350 0.83 0.24 ns T-test
6.0 FCoCntrl_M2 XX XO 0.0597904 0.36 0.06 ns T-test
12.0 FCoCntrl_M2 XX XO 0.2667290 0.83 0.27 ns T-test
24.0 FCoCntrl_M2 XX XO 0.1662781 0.83 0.17 ns T-test

Treatment Dose in Log2 scale log2(Treatment+1)

Treatment Doses as Factors

M1

T-test:Unpaired This comparison gave an error because the control replicate values were 1 ??

Ttest_pP70s6k_CTDR_Unpaired <- compare_means(FCoCntrl_M1 ~ Cell_line,
                                          data = CTDR_P70s6k_plot,
                                          method = "t.test",
                                          paired = FALSE,
                                          group.by = c("Treatment"),
                                          ref.group = NULL)

kable(Ttest_pP70s6k_CTDR_Unpaired)
Treatment .y. group1 group2 p p.adj p.format p.signif method
0.0 FCoCntrl_M1 XX XO 1.0000000 1.00 1.000 ns T-test
1.5 FCoCntrl_M1 XX XO 0.1721236 0.85 0.172 ns T-test
3.0 FCoCntrl_M1 XX XO 0.2385558 0.85 0.239 ns T-test
6.0 FCoCntrl_M1 XX XO 0.0324939 0.19 0.032 * T-test
12.0 FCoCntrl_M1 XX XO 0.2740605 0.85 0.274 ns T-test
24.0 FCoCntrl_M1 XX XO 0.1708718 0.85 0.171 ns T-test

T-test:Paired

Ttest_pP70s6k_CTDR_Paired <- compare_means(FCoCntrl_M1 ~ Cell_line,
                                           data = CTDR_P70s6k_plot,
                                           method = "t.test",
                                           paired = TRUE,
                                           group.by = c("Treatment"),
                                           ref.group = NULL)

kable(Ttest_pP70s6k_CTDR_Paired)
Treatment .y. group1 group2 p p.adj p.format p.signif method
0.0 FCoCntrl_M1 XX XO 1.0000000 1.00 1.00 ns T-test
1.5 FCoCntrl_M1 XX XO 0.3301041 1.00 0.33 ns T-test
3.0 FCoCntrl_M1 XX XO 0.2324780 1.00 0.23 ns T-test
6.0 FCoCntrl_M1 XX XO 0.1414416 0.85 0.14 ns T-test
12.0 FCoCntrl_M1 XX XO 0.3205950 1.00 0.32 ns T-test
24.0 FCoCntrl_M1 XX XO 0.2911853 1.00 0.29 ns T-test

Treatment Dose in Log2 scale log2(Treatment+1)

Treatment Doses as Factors

WritingCSV

write.csv(CTDR_Akt_FC, file = "OutputFiles/CTDR_Akt_FC.csv")
write.csv(CTDR_P70s6k_FC, file = "OutputFiles/CTDR_P70s6k_FC.csv")

PaperFigures

I am using the WB imgaes from R3,

  • for pAkt+ Akt : Gel 23 : 0000063_02_JuneGel23_CTDR_Aktp.png
  • for p70Rsk + TPS : Gel 20 : 0000045_02_JuneGel20_CTDR_p70S6K.png
CTDR_All <- dplyr::full_join(CTDR_Akt_plot, CTDR_P70s6k_plot, by=c("Cell_line","Replicate","Treatment","log2Treatment","Treatment_Fctr"), suffix = c("_Akt", "_P70s6k"))

CTDR_All <- CTDR_All %>%
  select(-c(grep("Analyte", colnames(CTDR_All))))

CTDR_All$Cell_line <- factor(CTDR_All$Cell_line, levels = c("XX", "XO", "nn"))

CTDR_Allplot <- CTDR_All %>% 
  select(c("Cell_line","Replicate","Treatment","log2Treatment","Treatment_Fctr",grep("FCoXX_M2",colnames(CTDR_All)))) %>% 
  gather(key = "Analyte", value = "Signal", -c("Cell_line","Replicate","Treatment","log2Treatment","Treatment_Fctr"))

Analyte_labels <- c("FCoXX_M2_Akt" = "pAkt", "FCoXX_M2_P70s6k" = "pP70s6k")

#### Setting up the plotting attributes ###
# MyCellLineColours <- c("XX" = "#FF0000", "XO" = "#0000CD", "nn" = "#000005")
# MyReplicateShapes <-  c("R1" = 2, "R2" = 0, "R3" = 6, "nn"= 4)

g <- Plot_TwoPanel_ValidationPlot_updated(CTDR_Allplot,"log2Treatment", "Signal" ,Analyte_labels,"fixed")+
  labs(x = "\nGsk3i(\u03bcM)+1 [log2]", #\u03bc is the unicode charachter fro greek mu
       y = "Rel. phosp. (norm.)\n",
       color = "Cell line" )  # color within labs,lets me give user defined labels to the attribute in legend
  

gt=set_panel_size(g,width=unit(2.8,'cm'),height=unit(2.8,'cm'))
grid.arrange(gt)

ggsave("CTDR_pAkt_pP70s6k_FCoXX_s15.pdf", gt, dpi=300, useDingbats=FALSE ,path = "./OutputFiles") # device = cairo_pdf was tried to get the greek letter in pdf, but not yet successful in that
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